Chlorophyll content and distribution in plant’s leaves is an important index in estimation of plant nutrition information. In the present work, chlorophyll content and distribution in tea plant’s leaves were measured by hyperspectral imaging technique. First, hyperspectral image data were captured from tea plant’s leaves; then seven kinds of algorithms were used to extract the characteristic parameters from hyperspectral image; finally, seven fitted models were developed using the characteristics vectors and the reference measurements of chlorophyll contents respectively. Experimental results showed that the MSAVI2 model is superior to other models, and the results of the MSAVI2 model was achieved as follows: R=0.843 3 and RMSE=9.918 in the calibration set; R=0.832 3 and RMSE=8.601 in the prediction set. Finally, the chlorophyll content of each pixel in image was estimated by the fitted model, and the distribution of chlorophyll content in the tea plant’s leaf was described by pseudo-color map. This study sufficiently demonstrated that the chlorophyll content and distribution in tea leaf can be measured by hyperspectral imaging technique.